code: def batch_l2_norm_squared(x):
      """L2 norm (a.k.a.\\  Euclidean norm) squared.
  
      This function implements the square of L2 norm on a vector. No reduction
      along batch axis is done.
  
      Args:
          x (:class:`~chainer.Variable` or :ref:`ndarray`): Input variable.
              The first dimension is assumed to be the *minibatch dimension*.
              If ``x`` has more than two dimensions all but the first dimension
              are flattened to one dimension.
  
      Returns:
          ~chainer.Variable: Two dimensional output variable.
  
      """
      return BatchL2NormSquared().apply((x,))[0]
  
file_path: chainer/chainer/functions/math/batch_l2_norm_squared.py
imports: import six
  import chainer
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.functions.math import sum
  from chainer.utils import type_check
label_desc: Use image node_id 1 for calling a global function with example usage: batch_l2_norm_squared(x) and returns: BatchL2NormSquared